Extraction of DNA and RNA from Formalin-fixed Paraffin-embedded Tissue Specimens

Shukla, Nidhi; Siva, Narmadhaa; Sivakumar, Madhu Balaji; Parveen, Rabia; Mishra, Ashwani Kumar; Shah, Avadh K.; Medicherla, Krishna Mohan; Suravajhala, Prashanth

doi:10.21769/bioprotoc.4095

Cited by 1 publication

(2 citation statements)

References 18 publications

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“…Although there has been difficulty in extracting RNA from FFPE blocks from the RNA-seq, which is usually the case [ 39 ], while checking it and downstream analyses, all samples yielded good quality reads from FastQC with ca. 40 M transcript reads with no exposure in tiles.…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, in our previous study, we performed WES on PCa samples, which we have cited, but again, the sample size is limited. (iv) Due to a lack of fresh–frozen prostate/radical prostatectomy tissues, only FFPE blocks were used, and isolating RNA from them is an arduous and challenging task [ 39 ]; due to this, we could not perform qRT-PCR for all the selected DEGs.…”

Section: Discussionmentioning

confidence: 99%

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Towards Understanding the Key Signature Pathways Associated from Differentially Expressed Gene Analysis in an Indian Prostate Cancer Cohort

et al. 2023

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Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with genetics, genomics, and the environmental influence in the causality of PCa, not many studies employing the Next Generation Sequencing (NGS) approaches of PCa have been carried out. In our previous study, we identified some causal genes and mutations specific to Indian PCa using Whole Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify differentially expressed genes (DEGs) including long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using the RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened six patients who underwent prostatectomy; we performed whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz., GeneMANIA, Stringdb, Cytoscape-Cytohubba, and cbioportal, to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa, such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, and HN1L, and some other important genes known to be involved in different cancer pathways, such as COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1, etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, ENSG00000287903, and ENST00000647843.1 that need to be characterized further. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which perhaps have not been reported. This has set a precedent for us to validate candidates further experimentally, and we firmly believe this will pave a way toward the discovery of biomarkers and the development of novel therapies.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%